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|Title: ||The utility of absolute risk prediction using FRAX (R) and Garvan Fracture Risk Calculator in daily practice|
|Authors: ||van Geel, Tineke A. C. M.|
Eisman, John A.
VAN DEN BERGH, Joop
Center, Jacqueline R.
|Issue Date: ||2014|
|Citation: ||MATURITAS, 77 (2), p. 174-179|
|Abstract: ||Objectives: There are two commonly used fracture risk prediction tools FRAX® and Garvan Fracture Risk Calculator (GARVAN-FRC). The objective of this study was to investigate the utility of these tools in daily practice.
Study design: A prospective population-based 5-year follow-up study was conducted in ten general practice centres in the Netherlands. For the analyses, the FRAX® and GARVAN-FRC 10-year absolute risks (FRAX® does not have 5-year risk prediction) for all fractures were used.
Results: Among 506 postmenopausal women aged ≥60 years (mean age: 67.8 ± 5.8 years), 48 (9.5%) sustained a fracture during follow-up. Both tools, using BMD values, distinguish between women who did and did not fracture (10.2% vs. 6.8%, respectively for FRAX® and 32.4% vs. 39.1%, respectively for GARVAN-FRC, p < 0.0001) at group level. However, only 8.9% of those who sustained a fracture had an
estimated fracture risk ≥20% using FRAX® compared with 53.3% using GARVAN-FRC. Although both underestimated the observed fracture risk, the GARVAN-FRC performed significantly better for women who sustained a fracture (higher sensitivity) and FRAX® for women who did not sustain a fracture (higher specificity). Similar results were obtained using age related cut off points.
Conclusions: The discriminant value of both models is at least as good as models used in other medical conditions; hence they can be used to communicate the fracture risk to patients. However, given differences in the estimated risks between FRAX® and GARVAN-FRC, the significance of the absolute risk must be related to country-specific recommended intervention thresholds to inform the patient.|
|Notes: ||van Geel, TACM (reprint author), Maastricht Univ, Dept Family Med, POB 616, NL-6200 MD Maastricht, Netherlands. firstname.lastname@example.org|
|ISI #: ||000331665300013|
|Type: ||Journal Contribution|
|Validation: ||ecoom, 2015|
|Appears in Collections: ||Research publications|
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